Machine Learning Applications in Business

Overview

Business Problem Solving Using Machine Learning

Maximum marks: 40 marks.

Turnitin similarity: 15% or less

AI similarity: Less than 20% or star

Report Length: 3,000–4,000 words

Presentation: 15 minutes

Submission Components:

o Project Report

o Dataset, if available

o Presentation Slides

o Individual Contribution Sheet

Academic Integrity Requirements

• The assignment must be the student's own work.

• All sources must be cited using APA.

• A minimum of 10 academic references (journal articles, books, industry reports, and

reputable business sources) is required.

• Plagiarism, contract cheating, and unauthorised copying will be penalised according

to university regulations.

Project Objective

1Students are required to identify a real-world business problem, apply machine learning

techniques to analyse data, apply predictive or descriptive models, and provide business

recommendations.

The project should demonstrate:

• Understanding of business problems

• Data collection and preparation

• Application of machine learning techniques

• Model evaluation

• Business interpretation of results

• Team collaboration

Suggested Project Topics

Students may choose one of the following:

Finance

• Loan default prediction

• Credit risk assessment

• Fraud detection

• Stock price movement prediction

Marketing

• Customer segmentation

• Customer churn or attrition prediction

• Product recommendation system

• Sales forecasting